This is a great idea. Something non-symmetric with very simple
analytic results would be perfect, particularly for this application
... I'm going through and adding answer tests for callbacks now, and
would be happy to add this on as well. We could start with something
just going slightly off-diagonal, which should be enough to
demonstrate it's correct.

Hi Matt, I've been thinking about the need for us to
create some special
verification datasets where we know what the right answer is, so we can test
the various routines, like the streamline plot, to see if we get the
expected plot. These should be conceptually simple datasets (like a
left-handed vortex of vectors) where we know what the result should look
like.

I had tried something earlier with a volume render dataset when I was
playing with left/right handedness. In that case, I had simply made my
dataset in NumPy as a cubic array and then fed it into yt -- that seems to
be an easy route to testing these things.

In debugging the streamline plot callback, I've run into something odd.
I'm hoping @jwise77 , who wrote it originally, might be able to chime in.

It's not clear to me that we are doing "the right thing" since we have an
image plot which is using origin='lower' and a streamline plot that is
not. Additionally, the x, y ordering requires us not to transpose the
resultant image buffers to get the right shape of our array, if we have a
non-unitary input buffer.

In short, I think the inputs may be transposed but shouldn't be, and I'm
not sure the streamplot is right.